NYULMC Molecular Outbreak Center


The Molecular Outbreak Center at NYU (MOC) provides an important tool to enhance clinical training and research opportunities for ID fellows at NYULMC. This center pioneers the emerging field of Health Care Epidemiology, combining antibiotic stewardship, infection prevention and control (IPC), molecular diagnostics, and molecular epidemiology. By implementing a surveillance system that links an automated statistical cluster detection system with technologies for molecular typing of isolates from infection clusters suspected of being related, the collaboration between the NYULMC IPC and MOC provides real-time data that can generate early warnings of potential healthcare associated infections and outbreaks. This Center thus provides opportunities to perform research that has important implications for patient safety and public health.

NYU Langone Medical Center Molecular Outbreak Center

Hospital and healthcare facility-associated infections are an increasing concern nationwide and worldwide. New York University Langone Medical Center (NYULMC) is leading the way in developing and applying new tools for detection and prevention of infections in our patients.

Our unique approach consists of a collaboration of Infection Prevention and Control (IPC), Clinical Microbiology and the newly-established Molecular Outbreak Center (MOC).

In late 2013, IPC initiated a system for the automated detection of clusters of infection and related antimicrobial resistance profiles at NYULMC. The system includes an information unit that analyzes microbiology culture and antimicrobial resistance data to generate alerts for groups of infection that exceed preset statistical parameters and suggest hospital-acquired infection clusters (outbreaks) (see www.satscan.org; or www.whonet.org). These clusters are investigated by infection control practitioners, and the MOC is notified.

The MOC employs state of the art and newly-developed technologies for high-resolution typing of isolates from infection clusters suspected of being related. Molecular typing complements automated cluster detection in the understanding of strain transmission. Linking information on genetic patterns of the infecting isolates with patients’ epidemiological information provides more definitive conclusions to confirm (or refute) the outbreak. Typing is particularly useful for organisms (such as methicillin-resistant Staphylococcus aureus [MRSA]) that are highly endemic in health care facilities, because even large outbreaks may be difficult to identify against the naturally fluctuating background incidence.

The combination of automated statistical cluster detection and molecular typing provide an early warning system for detecting transmission events which result in healthcare associated infections and outbreaks. The ability to detect transmission of pathogens within the hospital allows us to use rapid, focused infection prevention measures to prevent colonization of susceptible patients and subsequent infection. The information is also used to optimize use of contact precautions, which have inherent risks to patient safety.

Our staff includes epidemiologists, infection control practitioners, clinical microbiologists, molecular biologists, and mathematical modelers. In addition to our mission to prevent infections in our patients, we offer short and longer-term training and research opportunities.

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